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International Conference on Systems and control (ICSC)

作者： Bilel Dhouib Moncef Triki Mohamed Ali Zdiri Hsan Hadj Abdallah Electrical engineering department Sfax engineering school Control & energy management laboratory Sfax engineering school Sfax Tunisia Electrical Engineering Department Sfax laboratory of sciences and techniques of automatic & computer engineering (Lab-STA) Sfax engineering school Sfax Tunisia Electrical engineering department Sfax engineering school control & energy management laboratory Sfax engineering school Sfax Tunisia

With the increasing need for sustainable energy sources, wind power has gained prominence as a clean and renewable option. Nevertheless, incorporating wind power into the electrical grid at a significant scale can have a considerable impact on the dynamic behavior of the power system, leading to heightened operational uncertainties. The expanding requirement for power network connection to wind farms has led to the occurrence of rotor angle fluctuations and frequency instability. This paper utilizes a Static Synchronous Compensator (STATCOM) along with a multi-band power system stabilizer (MB-PSS) to assess the transient stability of a power grid. To demonstrate the system's efficiency under fault conditions, such as triple line-to-ground faults (LLLG), a nine-bus, three-machine test network incorporating a Doubly Fed Induction Generator (DFIG) has been employed. The system's performance has been evaluated through MATLAB/Simulink simulations, which reveal that the combination of STATCOM with MB-PSS produces superior results in enhancing transient stability when compared to the scenarios of using STATCOM alone or not using it at all.

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Safe trajectory tracking using closed-form controllers based on control barrier functions

Safe trajectory tracking using closed-form controllers based...

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IEEE Conference on Decision and control

作者： Andrea Cristofaro Marco Ferro Marilena Vendittelli Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper considers the problem of guaranteeing avoidance of critical state space regions during tracking of reference trajectories for systems with dynamics equivalent to r-th order decoupled integrators. The necessity to avoid those critical regions during trajectory tracking may arise during the transient phase or because the reference trajectory was planned without taking into account the presence of those critical regions. A typical problem in mobile robotics, taken as reference in this paper, is the avoidance of obstacles in the robot workspace during tracking of reference state space trajectories. The proposed controller ensures a safety clearance from the forbidden regions by filtering out, when appropriate, the component of the tracking command that would eventually lead the system to enter the critical region. The method relies on the construction of first-order control barrier functions and closed-form controllers, with formal proof of safety and stability, and its effective application to wheeled mobile robots and quadrotors is demonstrated through simulation.

关键词： Three-dimensional displays Trajectory tracking Euclidean distance Aerospace electronics Stability analysis Trajectory Safety

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An Extended Stochastic Region of Attraction Estimation Method for Power Systems Under Stochastic Sustained Disturbances

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IEEE Transactions on Power Systems 2025年

作者： Yang, Yuerong Lin, Shunjiang Liu, Mingbo Deng, Leyi Xie, Huifan Li, Qifeng South China University of Technology School of Electric Power Engineering Guangzhou510640 China Power Dispatching and Control Center CSG Guangzhou510663 China University of Central Florida Department of Electrical and Computer Engineering OrlandoFL32816 United States

Stochastic sustained disturbances (SSDs) in renewable energy output impact power system transient stability. This study addresses the dynamic performance of power systems under SSDs using Lévy-driven stochastic differential algebraic equations (LDSDAEs). The stochastic region of attraction for LDSDAEs is divided into a stable region and a probabilistically stable region, collectively termed the extended stochastic region of attraction (ESRA). Traditional methods for estimating the deterministic region of attraction (RA) are inadequate. To address this issue, this study proposes an estimation method for the ESRA of LDSDAEs based on escape probability. We first derive an integro-differential equation for escape probabilities of initial system states near the attractor of LDSDAEs. We then explore the connection between escape probability and ESRA. Finally, we propose a wavelet basis functions-based extended projection method to solve the integro-differential equation, providing an analytical expression for escape probabilities and thus determining the ESRA. Case studies on the modified IEEE 39- and 118-bus systems demonstrate the proposed method's high computational accuracy and efficiency for power systems under Lévy disturbances. © 1969-2012 IEEE.

关键词： Integrodifferential equations

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Explainable Artificial Intelligence Solution for Online Retail

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computers, Materials & Continua 2022年第6期71卷 4425-4442页

作者： Kumail Javaid Ayesha Siddiqa Syed Abbas Zilqurnain Naqvi Allah Ditta Muhammad Ahsan M.A.Khan Tariq Mahmood Muhammad Adnan Khan Department of Computer Science University of South AsiaLahore54000Pakistan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54000Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Division of Science and Technology University of EducationLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for *** the case of the online shopping business,it’s very important to find trends in the data and get knowledge of features that helps drive the success of the *** this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one *** main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the *** permutation feature importance approach has been used to get the importance of features according to the output variable(Revenue).Five ML models i.e.,decision tree(DT),random forest(RF),extra tree(ET)classifier,Neural networks(NN),and Logistic regression(LR)have been used to make predictions on the unseen data in the *** performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC *** model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree ***,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying *** research also reveals the importance of page value as a key feature for capturing online purchasing *** may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business.

关键词： Explainable artificial intelligence online retail neural network random forest regression

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Geometric Reachability for Attitude control Systems via Contraction Theory

arXiv

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arXiv 2025年

作者： Xu, Chencheng Jafarpour, Saber Zhao, Chengcheng Shi, Zhiguo Chen, Jiming College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO United States College of Control Science and Engineering Zhejiang University Hangzhou China

In this paper, we present a geometric framework for the reachability analysis of attitude control systems. We model the attitude dynamics on the product manifold SO(3) × 3 and introduce a novel parametrized family of Riemannian metrics on this space. Using contraction theory on manifolds, we establish reliable upper bounds on the Riemannian distance between nearby trajectories of the attitude control systems. By combining these trajectory bounds with numerical simulations, we provide a simulation-based algorithm to over-approximate the reachable sets of attitude systems. We show that the search for optimal metrics for distance bounds can be efficiently performed using semidefinite programming. Additionally, we introduce a practical and effective representation of these over-approximations on manifolds, enabling their integration with existing Euclidean tools and software. Numerical experiments validate the effectiveness of the proposed approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Geometry

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Spectral graph theory to investigate topological and dynamic properties of EEG-based brain networks: an application to post-stroke patients

Spectral graph theory to investigate topological and dynamic...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Andrea Ranieri Floriana Pichiorri Elena Mongiardini Emma Colamarino Febo Cincotti Donatella Mattia Jlenia Toppi Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Neuroelectrical Imaging and BCI Laboratory Fondazione Santa Lucia Hospital Rome Italy

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Brain networks represent one of the most fascinating biophysics contributions to modern medicine. Nowadays clinical practice largely benefits from network theory to characterize both physiological and pathological brain networks. However, to date the analysis of such systems still relies on classic approaches, thus limiting the amount of information extracted from those networks. As to overcome such a limitation, this work investigates the behavior of brain networks combinig combining both spectral graph theory and random walk analysis. Specifically, the algebraic connectivity and the relaxation time have been extracted from functional resting state brain networks estimated from a population of subacute post-stroke subjects. Results have been correlated with the Upper Extremity Fugl-Mayer Assessment (UEFMA) score of each subject as to assess whether a dependence exists between network’s organization and motor impairment in the upper limb.

关键词： Pathology Limiting Organizations Motors Graph theory Physiology Biophysics Data mining engineering in medicine and biology Network theory (graphs)

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CMALight: a novel Minibatch Algorithm for large-scale non convex finite sum optimization

arXiv

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arXiv 2023年

作者： Coppola, Corrado Liuzzi, Giampaolo Palagi, Laura Department of Computer Control and Management Engineering A. Ruberti - Sapienza University of Rome Via Ariosto 25 Rome00185 Italy

The supervised training of a deep neural network on a given dataset consists in the unconstrained minimization of the finite sum of continuously differentiable functions, commonly referred to as loss with respect to the samples. These functions depend on the network parameters and most of the times are non-convex. We develop CMA Light, a new globally convergent mini-batch gradient method to tackle this problem. We consider the recently introduced controlled Minibatch Algorithm (CMA) framework and we overcome its main bottleneck, removing the need for at least one evaluation of the whole objective function per iteration. We prove global convergence of CMA Lightunder mild assumptions and we discuss extensive computational results on the same experimental test-bed used for CMA, showing that CMA Lightrequires less computational effort than most of the state-of-the-art optimizers. Eventually, we present early results on a large-scale Image Classification task. © 2023, CC BY-NC-ND.

关键词： Gradient methods

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Driving the Change: How Do Personal Factors and Socio-Economic Context Influence Electric Vehicles Adoption Across Europe?

SSRN

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SSRN 2024年

作者： Schiaroli, Valerio Fraccascia, Luca Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome Via Ariosto 25 Rome Italy Department of High-Tech Business and Entrepreneurship University of Twente Netherlands

This paper investigates the determinants influencing consumer adoption of battery electric vehicles (BEVs) across three European markets characterized by distinct socio-economic contexts and varying levels of EV market maturity. We develop a theoretical model based on Theory of Planned Behavior. A survey was conducted involving 737 consumers in Germany, Italy, and Norway. The data was analyzed using structural equation modeling, multigroup analysis, and Kruskal-Wallis’s test. The findings indicate that hedonic motivations, ascription of responsibility, subjective norms, and direct experience significantly enhance consumers' willingness to purchase BEVs. Conversely, range anxiety and environmental concerns negatively affect purchase intentions. Significant differences in consumer perceptions of BEVs and the effect of behavioral determinants across the three countries are highlighted. This research contributes to the literature on sustainable mobility adoption and proposes several avenues for future investigation. The findings can inform the development of marketing strategies and policy interventions to foster EV adoption in Europe. © 2024, The Authors. All rights reserved.

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Cloud-Based DMPC Simulation for Autonomous Mobile Robot Platooning

Cloud-Based DMPC Simulation for Autonomous Mobile Robot Plat...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Anca Maxim Ovidiu Pauca Razvan-Gabriel Lazar Cristian-Mihai Amarandei Constantin-Florin Caruntu Department of Automatic Control and Applied Informatics "Gheorghe Asachi" Technical University of Iasi Iasi Romania Department of Computer Science and Engineering "Gheorghe Asachi" Technical University of Iasi Iasi Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

Cloud computing can be an useful tool when dealing with spatially distributed resources, which need to be simultaneously managed. In this work, a simulation environment is developed using OpenStack to apply a Distributed Model Predictive control strategy for a platooning application consisting of multiple autonomous mobile robots. The idea is to develop the entire algorithm by taking advantage of the possibility of creating virtual machines. Thus, each autonomous mobile robot is treated as an individual agent and is modeled and controlled on a virtual machine, whereas the communication between the agents is performed in the cloud, using the TCP/IP protocol standard. The simulation results illustrate that the platooning application deployed in OpenStack outperforms the simulation performed on a single computer.

关键词： Cloud computing Protocols Computational modeling Stability criteria TCPIP Mathematical models Mobile robots MATLAB Autonomous robots Testing

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Multi-Agent Coordination for a Partially Observable and Dynamic Robot Soccer Environment with Limited Communication

arXiv

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arXiv 2024年

作者： Affinita, Daniele Volpi, Flavio Spagnoli, Valerio Suriani, Vincenzo Nardi, Daniele Bloisi, Domenico D. Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Italy Faculty of Political Science and Sociopsychological Dynamics UNINT University Rome Italy

RoboCup represents an International testbed for advancing research in AI and robotics, focusing on a definite goal: developing a robot team that can win against the human world soccer champion team by the year 2050. To achieve this goal, autonomous humanoid robots’ coordination is crucial. This paper explores novel solutions within the RoboCup Standard Platform League (SPL), where a reduction in WiFi communication is imperative, leading to the development of new coordination paradigms. The SPL has experienced a substantial decrease in network packet rate, compelling the need for advanced coordination architectures to maintain optimal team functionality in dynamic environments. Inspired by market-based task assignment, we introduce a novel distributed coordination system to orchestrate autonomous robots’ actions efficiently in low communication scenarios. This approach has been tested with NAO robots during official RoboCup competitions and in the SimRobot simulator, demonstrating a notable reduction in task overlaps in limited communication settings. © 2024, CC BY.

关键词： Human resource management

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